I pretty miss some predict functionality in censReg, that would at provide fitted values. And to be constructive, I am appending code, which seems to be pretty robust for usage :) (do not know how slow it is, but I use it regularly and serves well)

(just replace model.tobit by generic model and data3 by name of the provided dataset and probably some functionality which would care about if there is a constatnt in the model - honestly, I am not sure if censored models without constant make any sense )

# Get coefficientscoefficients <- summary(model.tobit)$estimate[1:(length(summary(model.tobit)$estimate[,1])-1),1]# Get names of the coefficientsnames <- names(coefficients)# Find indices of the namesindices <- unlist(lapply(names[-1], function(x) which(colnames(data3)==x)))# Check if they exist in the dataset (if they were found)if (length(indices)==(length(coefficients)-1)) { # Add constant term and construct dataset data <- cbind(rep(1, length(data3[,1])), do.call(cbind, lapply(indices, function(x) data3[,x]))) # Make the predicted values fitted <- (data %*% coefficients)[,1]} else { warning("The dataset does not contain some of the variables.")}